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Dangerous omissions: the consequences of ignoring decision uncertainty

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  • Susan C. Griffin
  • Karl P. Claxton
  • Stephen J. Palmer
  • Mark J. Sculpher

Abstract

Institutions with the responsibility for making adoption (reimbursement) decisions in health care often lack the remit to demand or commission further research: adoption decisions are their only policy instrument. The decision to adopt a technology also influences the prospects of acquiring further evidence because the incentives to conduct research are reduced and the ethical basis of further clinical trials maybe undermined. In these circumstances the decision maker must consider whether the benefits of immediate access to a technology exceeds the value of the evidence which maybe forgone for future patients. We outline how these expected opportunity losses can be established from the perspective of a societal decision maker with and without the remit to commission research, and demonstrate how these considerations change the appropriate decision rules in cost‐effectiveness analysis. Importantly, we identify those circumstances in which the approval of a technology that is expected to be cost‐effective should be withheld, i.e. when an ‘only in research’ recommendation should be made. We demonstrate that a sufficient condition for immediate adoption of a technology can provide incentives for manufacturers to reduce the price or provide additional supporting evidence. However, decisions based solely on expected net benefit provide no such incentives, may undermine the evidence base for future clinical practice and reduce expected net health benefits for the patient population. Copyright © 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • Susan C. Griffin & Karl P. Claxton & Stephen J. Palmer & Mark J. Sculpher, 2011. "Dangerous omissions: the consequences of ignoring decision uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 212-224, February.
  • Handle: RePEc:wly:hlthec:v:20:y:2011:i:2:p:212-224
    DOI: 10.1002/hec.1586
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    References listed on IDEAS

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    1. Palmer, Stephen & Smith, Peter C., 2000. "Incorporating option values into the economic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 19(5), pages 755-766, September.
    2. Zoe Philips & Karl Claxton & Stephen Palmer, 2008. "The Half-Life of Truth: What Are Appropriate Time Horizons for Research Decisions?," Medical Decision Making, , vol. 28(3), pages 287-299, May.
    3. A. E. Ades & G. Lu & K. Claxton, 2004. "Expected Value of Sample Information Calculations in Medical Decision Modeling," Medical Decision Making, , vol. 24(2), pages 207-227, March.
    4. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216, February.
    5. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    6. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
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    Cited by:

    1. Bognar, Katalin & Romley, John A. & Bae, Jay P. & Murray, James & Chou, Jacquelyn W. & Lakdawalla, Darius N., 2017. "The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions," Journal of Health Economics, Elsevier, vol. 51(C), pages 1-12.
    2. Andrija S Grustam & Nasuh Buyukkaramikli & Ron Koymans & Hubertus J M Vrijhoef & Johan L Severens, 2019. "Value of information analysis in telehealth for chronic heart failure management," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-23, June.
    3. Gandjour, Afschin & Chernyak, Nadja, 2011. "A new prize system for drug innovation," Health Policy, Elsevier, vol. 102(2), pages 170-177.
    4. Levaggi, R. & Moretto, M. & Pertile, P., 2012. "Static and dynamic efficiency of irreversible health care investments under alternative payment rules," Journal of Health Economics, Elsevier, vol. 31(1), pages 169-179.
    5. Laura Bojke & Marta O. Soares & Karl Claxton & Abigail Colson & Aimée Fox & Chris Jackson & Dina Jankovic & Alec Morton & Linda D. Sharples & Andrea Taylor, 2022. "Reference Case Methods for Expert Elicitation in Health Care Decision Making," Medical Decision Making, , vol. 42(2), pages 182-193, February.
    6. David D. Kim & Anirban Basu, 2017. "New Metrics for Economic Evaluation in the Presence of Heterogeneity: Focusing on Evaluating Policy Alternatives Rather than Treatment Alternatives," Medical Decision Making, , vol. 37(8), pages 930-941, November.
    7. Kisser, Agnes & Tüchler, Heinz & Erdös, Judit & Wild, Claudia, 2016. "Factors influencing coverage decisions on medical devices: A retrospective analysis of 78 medical device appraisals for the Austrian hospital benefit catalogue 2008–2015," Health Policy, Elsevier, vol. 120(8), pages 903-912.
    8. Kasper M. Johannesen & Karl Claxton & Mark J. Sculpher & Allan J. Wailoo, 2018. "How to design the cost‐effectiveness appraisal process of new healthcare technologies to maximise population health: A conceptual framework," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 41-54, February.
    9. Campillo-Artero, Carlos, 2013. "A full-fledged overhaul is needed for a risk and value-based regulation of medical devices in Europe," Health Policy, Elsevier, vol. 113(1), pages 38-44.
    10. Martin Forster & Paolo Pertile, 2013. "Optimal decision rules for HTA under uncertainty: a wider, dynamic perspective," Health Economics, John Wiley & Sons, Ltd., vol. 22(12), pages 1507-1514, December.
    11. Levaggi, Rosella, 2014. "Pricing schemes for new drugs: A welfare analysis," Social Science & Medicine, Elsevier, vol. 102(C), pages 69-73.
    12. Anirban Basu & David Meltzer, 2018. "Decision Criterion and Value of Information Analysis: Optimal Aspirin Dosage for Secondary Prevention of Cardiovascular Events," Medical Decision Making, , vol. 38(4), pages 427-438, May.

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